Methods and systems for estimating motion in multimedia pictures

ABSTRACT

Several methods and systems for estimating motion in a plurality of multimedia pictures are disclosed. In an embodiment, at least one temporal distance between a multimedia picture and one or more reference pictures corresponding to the multimedia picture in a capture order associated with the plurality of multimedia pictures is computed. The at least one temporal distance is computed subsequent to an encoding of the multimedia picture. At least one motion estimation parameter is determined based on the at least one temporal distance. Motion associated with a subsequent multimedia picture to be encoded is estimated based on the at least one motion estimation parameter.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of provisional patent applicationnumber 1294/CHE/2011, filed on Apr. 14, 2011, in the Indian PatentOffice, which is incorporated herein by reference in its entirety.

TECHNICAL FIELD

The present disclosure generally relates to the field of motionestimation.

BACKGROUND

Pursuant to an exemplary scenario, multimedia data, such as videocontent, may include a plurality of multimedia pictures (e.g.,multimedia frames or fields), and each multimedia picture may includeseveral blocks of data. During an encoding of the multimedia data, aprediction for each block of multimedia data may be performed based onpreviously encoded blocks of multimedia data, either from a currentmultimedia picture (e.g., intra prediction) or from another multimediapicture that has already been encoded and transmitted (e.g., interprediction). Identifying a suitable inter prediction may be referred to,for example, as motion estimation, and subtracting the inter predictionfrom the current block may be referred to, for example, as motioncompensation. The motion estimation/compensation may be implemented soas to achieve a multimedia data compression by eliminating a temporalredundancy based on a correlation between multimedia pictures.

SUMMARY

Various methods and systems for estimating motion in multimedia picturesare disclosed. In an embodiment, a method for estimating motion in aplurality of multimedia pictures is provided. The method, performed by aprocessor, includes computing at least one temporal distance between amultimedia picture and one or more reference pictures corresponding tothe multimedia picture in a capture order associated with the pluralityof multimedia pictures. The term ‘temporal distance’, as used herein,may be construed as referring to a positional difference between a pairof multimedia pictures arranged in a capture order. The temporaldistance may be computed in terms of temporal distance units. The atleast one temporal distance is computed subsequent to an encoding of themultimedia picture. In an embodiment, a minimum temporal distance fromamong the at least one temporal distance between the multimedia pictureand the one or more reference pictures is computed.

In an embodiment, the minimum temporal distance is compared with apreselected temporal distance value. In an embodiment, at least onemotion estimation parameter is determined based on the at least onetemporal distance. In an embodiment, the multimedia picture is selectedas a source picture for computing at least one motion estimationparameter upon determining that the minimum temporal distance is lessthan or equal to the preselected temporal distance value. Upon selectionof the multimedia picture as the source picture, the at least one motionestimation parameter is computed from the multimedia picture. The atleast one motion estimation parameter includes at least one of a set oftemporal predictors and a mean motion vector. The mean motion vectorcorresponds to a mean of all motion vectors in one or more regions ofinterest of the source picture selected for computing at least onemotion estimation parameter for estimating motion in a subsequentmultimedia picture. In an embodiment, each of the one or more regions ofinterest includes one or more blocks (e.g., macro blocks) within thesource picture. In an embodiment, motion in a subsequent multimediapicture to be encoded is estimated based on the computed at least onemotion estimation parameter. Upon determining that the minimum temporaldistance is greater than a preselected temporal distance value, motionassociated with the subsequent multimedia picture is estimated based ona preselected at least one motion estimation parameter.

Additionally, in an embodiment, a system for estimating motion inmultimedia pictures is provided. The system includes a processor moduleand a motion estimation module. The processor module is configured tocompute at least one temporal distance between a multimedia picture andone or more reference pictures corresponding to the multimedia picturein a capture order associated with the plurality of multimedia pictures.The at least one temporal distance is computed subsequent to an encodingof the multimedia picture. The motion estimation module iscommunicatively associated with the processor module and is configuredto determine at least one motion estimation parameter based on the atleast one temporal distance. The motion estimation module is alsoconfigured to estimate motion in a subsequent multimedia picture to beencoded based on the at least one motion estimation parameter.

Moreover, in an embodiment, a computer-implemented method of estimatingmotion in a plurality of multimedia pictures is provided. The methodincludes computing a minimum temporal distance from among at least onetemporal distance between the multimedia picture and the one or morereference pictures corresponding to the multimedia picture in a captureorder associated with the plurality of multimedia pictures, wherein theat least one temporal distance is computed subsequent to an encoding ofthe multimedia picture. The method also includes comparing the minimumtemporal distance with a preselected temporal distance valuecorresponding to two or more temporal distance units. The method furtherincludes performing one of selecting the multimedia picture as a sourcepicture for computing at least one motion estimation parameter upondetermining that the minimum temporal distance is less than or equal tothe preselected temporal distance value and estimating motion in thesubsequent multimedia picture based on a preselected at least one motionestimation parameter upon determining that the minimum temporal distanceis greater than a preselected temporal distance value.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 illustrates an overview of a multimedia data encoding processaccording to an exemplary scenario;

FIG. 2 is a block diagram of an exemplary system for estimating motionin multimedia pictures according to an embodiment;

FIG. 3 illustrates a plurality of multimedia pictures arranged in anexemplary capture order, according to an embodiment;

FIG. 4 illustrates an exemplary scheme for selecting a source picturefrom among the plurality of multimedia pictures of the hierarchicalcoding structure of FIG. 3, according to an embodiment;

FIG. 5 is a schematic view illustrating an exemplary adaptive fieldreferencing pattern that may be implemented to encode interlacedmultimedia content according to an embodiment;

FIGS. 6A and 6B illustrate an improvement of a perceptual multimediaquality on performing a source picture selection as explained in FIG. 4,pursuant to an exemplary scenario;

FIG. 7 is a flow diagram of a method of performing motion estimation ina plurality of multimedia pictures according to an embodiment; and

FIGS. 8A and 8B depict a flow diagram of a method of source pictureselection that may be implemented to estimate motion in a plurality ofmultimedia pictures according to an embodiment.

DETAILED DESCRIPTION

Pursuant to an exemplary scenario, a motion estimation/compensationprocedure is performed so as to achieve a multimedia data compression byeliminating a temporal redundancy based on a correlation betweenmultimedia pictures. The motion estimation for a multimedia picture isperformed based on a previously encoded multimedia picture. Themultimedia pictures may include, for example, multimedia frames, fields(e.g., a top field or a bottom field of interlaced multimedia content),and the like. In certain exemplary applications, the most recentlyencoded predictive picture (which may be referred to as the “P-picture”)is selected for estimating motion in the multimedia pictures until thenext P-picture is encoded. There may be significant amount of motioninvolved and/or a sizable change in intensity between two P-pictures,and estimating motion in the multimedia pictures based on the previouslyencoded P-picture at a large temporal distance from the multimediapictures may be sub-optimal. Various embodiments of the presenttechnology, however, provide systems and methods for estimating motionin multimedia pictures that are capable of overcoming these and otherobstacles and providing additional benefits

The following description and accompanying figures demonstrate that thepresent technology may be practiced, or otherwise implemented, in avariety of different embodiments. It should be noted, however, that thescope of the present technology is not limited to any or all of theembodiments disclosed herein. Indeed, one or more of the devices,features, operations, processes, characteristics, or other qualities ofa disclosed embodiment may be removed, replaced, supplemented, orchanged.

FIG. 1 illustrates an overview of a multimedia data encoding process inaccordance with an exemplary scenario. More particularly, FIG. 1illustrates a simplified overview of an encoding process flow 100 forencoding multimedia data 102. Pursuant to an exemplary scenario, amultimedia encoder may perform the encoding process flow 100 so as toachieve a compression of the multimedia data 102. The multimedia data102 may be compressed so as to efficiently utilize a storage capacityduring storage or a spectrum/bandwidth during transmission.

The multimedia encoder may be configured within a multimedia system.Examples of the multimedia system may include, but are not limited to,(1) multimedia devices, such as, for example, cellular phones, digitalvideo cameras and digital camcorders; (2) data processing devices, suchas, for example, personal computers, laptops and personal digitalassistants; and (3) consumer electronics, such as, for example, set topboxes, digital video disk (DVD) players and video network servers.Pursuant to an exemplary scenario, the multimedia encoder may be anymachine capable of executing a set of instructions (sequential and/orotherwise) so as to perform an encoding of multimedia data.

The multimedia data 102 may be received by the multimedia encoder from amedia capture device. Examples of a media capture device may include,but are not limited to, a video camera and a camcorder. The mediacapture device may be, for example, a stand-alone device or a part of amobile device, such as, for example, a Smartphone, or a data processingdevice, such as, for example, a personal computer, a laptop device or apersonal digital assistant (PDA). The multimedia data 102 may also bereceived by the multimedia encoder from a transcoding system, which maybe a stand-alone device or a part of a media capture device. Examples ofmultimedia data 102 may include, for example, video data, image data,audio-video data, graphical data, textual data or any combinationthereof.

Pursuant to an exemplary scenario, the multimedia data 102 may include aplurality of multimedia pictures, and each multimedia picture from amongthe plurality of multimedia pictures may include several blocks of data.During motion estimation/compensation 104 of the encoding process flow100, a prediction for each block from among a number of blocks ofmultimedia data 102 is determined and subtracted from the block so as toform residual multimedia data. The prediction for each block ofmultimedia data 102 may be performed based on previously encoded blocksof multimedia data 102, either from a current frame (e.g., intraprediction) or from other frames that have already been encoded andtransmitted (e.g., inter prediction). Identifying a suitable interprediction may be referred to, for example, as “motion estimation”, andsubtracting the inter prediction from the current block may be referredto, for example, as “motion compensation”.

After motion estimation/compensation 104, and duringtransformation/quantization 106, the residual multimedia data istransformed and quantized. The transformation of the residual multimediadata outputs a set of transform coefficients, each of which is aweighting value for a standard basis pattern. The weighted basispatterns, when combined, are capable of recreating the residualmultimedia data. The set of transform coefficients are then quantized(such as where each coefficient is scaled corresponding to a scale-downfactor which may be a mathematical reciprocal of the scale-up factorspecified by a multimedia standard, thereby effectively setting a numberof transform coefficients to a relatively small value (including a zerovalue)) so as to achieve compression.

The quantized transform coefficients, along with certain information(such as, for example, information about the structure of compresseddata, information about a complete sequence of multimedia data 102and/or information that enables a decoder to re-create the prediction),are subject to entropy encoding 108 (e.g., conversion into binary codesusing variable length coding and/or arithmetic coding). The entropyencoding 108 of the multimedia data 102 produces an efficient, compactand binary representation of the information in the form of encodedmultimedia data 110. The encoded multimedia data 110 may then be storedand/or transmitted. A system for estimating motion in a plurality ofmultimedia pictures, such as during motion estimation/compensation 104of the encoding process flow 100, is described in FIG. 2.

FIG. 2 is a block diagram of an exemplary system 200 for estimatingmotion in a plurality of multimedia pictures, according to anembodiment. In an embodiment, the system 200 is configured to beincluded within a multimedia encoder. In an embodiment, the system 200may be communicatively associated with a multimedia encoder such that aplurality of multimedia pictures may be received and such that motioncompensated multimedia pictures may be provided to the multimediaencoder. The plurality of multimedia pictures may include, for example,multimedia frames, fields (e.g., a top field or a bottom field of aninterlaced multimedia content), and the like. Furthermore, the pluralityof multimedia pictures may be associated with various multimedia contenttypes, such as, for example, progressive multimedia content, interlacedmultimedia content, and the like. In an exemplary embodiment, the system200 may be configured within a personal computer (PC), a tablet PC, aPDA, a mobile communication device, a web appliance, a set-top box(STB), an embedded system and/or any machine capable of executing a setof instructions (sequential and/or otherwise) so as to perform selectionof a multimedia picture as a source picture for computation of at leastone motion estimation parameter for motion estimation in the pluralityof multimedia pictures.

The term ‘source picture’, as used herein, may be construed as referringto a multimedia picture from among the plurality of multimedia pictures,selected for computing at least one motion estimation parameter forperforming motion estimation in a subsequent multimedia picture in anencoding order associated with the plurality of multimedia pictures. Theat least one motion estimation parameter includes at least one of a setof temporal predictors and a mean motion vector. The mean motion vectorcorresponds to a mean of all motion vectors in one or more regions ofinterest of the source picture. In an embodiment, each of the one ormore regions of interest includes one or more blocks (e.g., macroblocks) within the source picture. The at least one motion estimationparameter may be selected based on a backward reference picture (e.g., atemporally succeeding reference picture in the encoding order)associated with the source picture or a forward reference picture (e.g.,a temporally preceding reference picture in the encoding order)associated with the source picture.

In an embodiment, the system 200 includes a processor module 202, amotion estimation module 204, a memory module 206 and an encoding module208. In an embodiment, the processor module 202, the motion estimationmodule 204, the memory module 206 and/or the encoding module 208 areconfigured to communicate with each other via or through a bus 210.Examples of the bus 210 may include, but are not limited to, a data bus,an address bus, a control bus, and the like. The bus 210 may be, forexample, a serial bus, a bi-directional bus or a unidirectional bus.Examples of the memory module 206 may include, but are not limited to,random access memory (RAM), dual port RAM, synchronous dynamic RAM(SDRAM), double data rate SDRAM (DDR SDRAM), and the like. In anembodiment, the encoding module 208 may include one of an entropyencoder, as explained herein with reference to FIG. 1, and an encoderconfigured with the transformation/quantization and entropy encodingcapabilities.

In an embodiment, the processor module 202 may be configured to receivea plurality of multimedia pictures along with capture order informationand encoding order information. The plurality of multimedia pictures,along with the capture order information and the encoding orderinformation, may be stored in the memory module 206 or may be receivedfrom an external storage device, such as, for example, an externalmemory or a memory location within a media capture device, such as, forexample, a camera device. The processor module 202 is configured tocompute at least one temporal distance between a multimedia picture andone or more reference pictures corresponding to the multimedia picturein a capture order associated with the plurality of multimedia pictures.The computation of the one or more temporal distances between amultimedia picture and one or more reference pictures is explainedherein with reference to FIG. 3. The processor module 202 is furtherconfigured to compare the minimum temporal distance with a preselectedtemporal distance value.

During an initiation of an encoding of the multimedia pictures that arearranged in a capture order sequence, the preselected temporal distancevalue may be initially set to a value equal to or greater than atemporal distance between a first multimedia picture and a referencepicture associated with the first multimedia picture, wherein the firstmultimedia picture is a first picture from among a plurality ofmultimedia pictures corresponding to a group of pictures (GOP) alignedto be encoded in an encoding order. In an embodiment, the preselectedtemporal distance value is chosen to be greater than or equal to twotemporal distance units for an adaptive field referencing patternencoding of the plurality of multimedia pictures. Motion estimation of aplurality of multimedia pictures subjected to the adaptive fieldreferencing pattern encoding is described further in FIG. 5.

The processor module 202 is further configured to select the multimediapicture as a source picture for computing at least one motion estimationparameter upon or subsequent to determining that the minimum temporaldistance is less than or equal to the preselected temporal distancevalue. The selection of the source picture is explained further hereinwith reference to FIG. 4. The motion estimation module 204 is configuredto determine at least one motion estimation parameter from themultimedia picture upon or subsequent to selection of the multimediapicture as the source picture. In an embodiment, the motion estimationmodule 204 determines the at least one motion estimation parameter basedon a backward reference picture (e.g., a temporally succeeding referencepicture in an encoding order) associated with the multimedia pictureselected as the source picture. In an embodiment, the motion estimationmodule 204 determines the at least one motion estimation parameter basedon a forward reference picture (e.g., a temporally preceding referencepicture in the encoding order) associated with the multimedia pictureselected as the source picture.

In an embodiment, the motion estimation module 204 is configured toupdate the preselected temporal distance value to a value correspondingto the minimum temporal distance and/or update a preselected at leastone motion estimation parameter to at least one motion estimationparameter computed from the selected multimedia picture that may beimplemented to estimate motion in the subsequent multimedia picture. Theupdating may be performed upon or subsequent to selection of themultimedia picture as the source picture. In an embodiment, thepreselected temporal distance and the preselected at least one motionestimation parameter and/or their subsequent updated values may bestored in the memory module 206. In an embodiment, upon or subsequent toselection of an adaptive field referencing pattern that may beimplemented to encode multimedia pictures, the preselected at least onemotion estimation parameter is updated, and the preselected temporaldistance value is maintained at a value greater than or equal to twotemporal distance units. The motion estimation module 204 is configuredto estimate motion in the subsequent multimedia picture based on thepreselected at least one motion estimation parameter upon or subsequentto determining that the minimum temporal distance is greater than apreselected temporal distance value.

The encoding module 208 is configured to encode the subsequentmultimedia pictures based on the estimated motion in the subsequentmultimedia pictures. In an embodiment, the system 200 may additionallyinclude other components (not shown), such as, for example, an inputunit (e.g., a multimedia processing device), a video display unit (e.g.,a liquid crystals display (LCD), a cathode ray tube (CRT), and thelike), a cursor control device (e.g., a mouse), a drive unit (e.g., adisk drive), a signal generation unit (e.g., a speaker) and/or a networkinterface unit. The drive unit includes a machine-readable medium uponwhich is stored one or more sets of instructions (e.g., software)embodying one or more of the methodologies and/or functions describedherein. In an embodiment, the software resides, either completely orpartially, within the memory module 206 and/or the processor module 202,and/or within the motion estimation module 204, during the executionthereof by the system 200 such that the processor module 202, the motionestimation module 204 and/or the memory module 206 also constitutemachine-readable media.

The software may further be transmitted and/or received over a networkvia or through the network interface unit. The term “machine-readablemedium” may be construed to include a single medium and/or multiplemedia (e.g., a centralized and/or distributed database, and/orassociated caches and servers) that store the one or more sets ofinstructions. Moreover, the term “machine-readable medium” may beconstrued to include any medium that is capable of storing, encodingand/or carrying a set of instructions that may be executed by the system200 such that the execution of these instructions causes the system 200to perform one or more of the methodologies of the various embodiments.Furthermore, the term “machine-readable medium” may be construed toinclude, but shall not be limited to, solid-state memories, optical andmagnetic media, and carrier wave signals.

FIG. 3 illustrates a plurality of multimedia pictures arranged in anexemplary capture order, according to an embodiment. More particularly,FIG. 3 depicts a hierarchical coding structure 300 that includes aplurality of multimedia picture 302 in a capture order sequence 304. Ahierarchical coding structure 300 is defined to include a key pictureand a plurality of pictures that are temporally located between the keypicture and a previous key picture. Examples of the key picture mayinclude, but is not limited to, an intra coded picture (I-picture), aninstantaneous decoding refresh picture (IDR-picture), or a predictivepicture (P-picture). The plurality of multimedia pictures 302 of thehierarchical coding structure 300 includes multimedia pictures IDR₀, B₁,B₂, B₃, B₄, B₅, B₆, B₇, P₈, B₉, B₁₀, B₁₁, B₁₂, B₁₃, B₁₄, B₁₅, and P₁₆.The arrows, such as arrows 306, depicted in FIG. 3 illustrate adependence (or an association) of a multimedia picture on (or with)other multimedia pictures, such that a reference for encoding purposesis established. For example, the multimedia picture B₃ references themultimedia pictures B₂ and B₄, and the multimedia picture B₄ referencesthe multimedia pictures IDR₀ and P₈, for encoding purposes.

Temporal levels 308 associated with the respective multimedia picturesare also depicted in FIG. 3. For example, multimedia pictures B₁, B₃,B₅, B₇, B₉, B₁₁, B₁₃, and B₁₅ are associated with temporal level 4,multimedia pictures B₂, B₆, B₁₀, and B₁₄ are associated with temporallevel 3, multimedia pictures B₄ and B₁₂ are associated with temporallevel 2, and the multimedia pictures IDR₀, P₈ and P₁₆ are associatedwith temporal level 1. As explained herein with reference to FIG. 2, theprocessor module 202 is configured to compute at least one temporaldistance between a multimedia picture and one or more reference picturesassociated with the multimedia picture in a capture order associatedwith the plurality of multimedia pictures. The processor module 202 isfurther configured to determine a minimum temporal distance from amongthe at least one temporal distance between the multimedia picture andthe one or more reference pictures. The temporal distance is computedsubsequent to the encoding of the multimedia picture. The term ‘temporaldistance’, as used herein, may be construed, for example, as referringto a positional difference between a pair of multimedia pictures in thecapture order sequence 304. The temporal distance may be computed interms of temporal distance units.

A temporal distance unit of one may correspond to a time gap between acapture of a first multimedia picture and a second multimedia picturecaptured immediately before or subsequent to the capture of the firstmultimedia picture. For example, a reference picture for the multimediapicture P₈ is IDR₀. A temporal distance between the multimedia pictureP₈ and IDR₀ in the capture order sequence 304 is accordingly computed tobe 8 temporal distance units. A bi-directional picture (which may bereferred to as a “B-picture”) may refer to a pair of reference picturesand, correspondingly, is associated with a pair of temporal distancescorresponding to the pair of reference pictures (e.g., a first temporaldistance between the B-picture and a first reference picture and asecond temporal distance between the B-picture and a second referencepicture). The processor module 202 is configured to (1) determine whichof the first temporal distance and the second temporal distance is lowerand (2) identify the lesser of the first temporal distance and thesecond temporal distance as the minimum temporal distance. For example,if a temporal distance for the B-picture is 2 temporal distance units ina forward reference direction and 4 temporal distance units in abackward reference direction, then a minimum of the two temporaldistances, i.e. 2 temporal distance units, is selected as the minimumtemporal distance.

If a temporal distance in the forward reference direction and thebackward reference direction is equal, then a minimum temporal distancemay be selected to be one of the two temporal distance units. Forexample, the B-picture B₄ references multimedia pictures IDR₀ and P8,and a temporal distance can accordingly be computed to be 4 temporaldistance units in the forward reference direction and the backwardreference direction. Accordingly, the minimum temporal distance may becomputed to be 4 temporal distance units. The processor module 202 isfurther configured to select a multimedia picture as a source picturefor computing at least one motion estimation parameter for motionestimation in the subsequent multimedia picture, the selection performedbased on the minimum temporal distance. The selection of a multimediapicture as the source picture is explained herein with reference to FIG.4.

FIG. 4 illustrates an exemplary scheme 400 for selecting a sourcepicture from among the plurality of multimedia pictures of thehierarchical coding structure 300 of FIG. 3, according to an embodiment.More particularly, FIG. 4 depicts the capture order sequence 304, anencoding order sequence 406 and a subsequent source picture selectionorder 408 for the plurality of multimedia pictures 302 of FIG. 3. In anembodiment, the plurality of multimedia pictures 302 are received alongwith the capture order sequence 304 and the encoding order sequence 406by the processor module 202. Initially, at least one preselected motionestimation parameter is set to a minimum initial value (e.g., (0, 0),wherein each of the temporal predictors and the mean motion vector areset to 0) and the preselected temporal distance value is set to a largevalue, such as, for example, 100. The first multimedia picture in theencoding order is P₈. The motion estimation/compensation for P₈ isperformed by computing temporal predictors and a mean motion vector byreferring to IDR₀. The multimedia picture P₈ is then encoded (e.g.,using the encoding module 208) based on the computed temporal predictorsand the mean motion vector.

Upon encoding the multimedia picture P₈, a temporal distance between P₈and reference picture associated with P₈ (e.g. IDR₀) is computed as 8temporal distance units. In one embodiment, the computed temporaldistance for P₈ may correspond to the minimum temporal distance value(since P₈ has a single corresponding reference picture). The minimumtemporal distance value (e.g., 8) is compared with the preselectedminimum temporal distance value, such as, for example, 100. Upon orsubsequent to determining that the minimum temporal distance is lessthan the preselected temporal distance value, P₈ is selected as a sourcepicture for computing at least one motion estimation parameter from P₈to be used for encoding a number (e.g., one or more) of subsequentmultimedia pictures. Furthermore, the preselected temporal distancevalue is updated to 8 temporal distance units based on a temporaldistance between P₈ and the reference picture associated with P₈ (e.g.,IDR₀). At least one motion estimation parameter (e.g., a set of temporalpredictors and a mean motion vector) is determined from the selectedsource picture P₈, and the at least one preselected motion estimationparameter is updated based on the motion estimation parametersdetermined from P₈.

Subsequently, a second multimedia picture B₄ that is to be encodedpursuant to the encoding order sequence 406 is encoded, such as, forexample, by the encoding module 208, based on the at least motionparameter determined from the selected source picture P₈. Upon orsubsequent to an encoding of B₄, the processor module 202 computes atleast one temporal distance between B₄ and one or more referencepictures associated with B₄ in the capture order sequence 302. Accordingto the capture order sequence 302, the reference pictures for B₄ are P₈and IDR₀, and, accordingly, the temporal distance values are computed tobe 4 in both a forward reference region and a backward reference region.Accordingly, the minimum temporal distance is computed to be 4. Theminimum temporal distance of 4 is compared with the updated preselectedtemporal distance value of 8, and, upon or subsequent to determiningthat minimum temporal distance value is less than the updatedpreselected temporal distance value of 8, B₄ is selected as the sourcepicture for computing at least one motion estimation parameter from B₄that may be used to encode a number (e.g., one or more) of subsequentmultimedia pictures. The preselected temporal distance value is updatedto 4, and the at least one motion parameter is updated to at least onemotion parameter determined from the selected source picture B₄.

Subsequently, a third multimedia picture B₂ that is to be encodedpursuant to the encoding order sequence 406 is encoded, such as, forexample, by the encoding module 208, based on the at least one motionparameter that is determined from the selected source picture B₄. Uponor subsequent to an encoding of the third multimedia picture B₂, theprocessor module 202 computes at least one temporal distance between B₂and one or more reference pictures associated with B₂ in the captureorder sequence 302. According to the capture order sequence 302, thereference pictures for B₂ are B₄ and IDR₀, and, accordingly, thetemporal distance values are computed to be 2 in both the forward andbackward reference regions. Accordingly, the minimum temporal distanceis computed to be 2. The minimum temporal distance of 2 is compared withthe updated preselected temporal distance value of 4, and upon orsubsequent to determining that the minimum temporal distance value isless than the updated preselected temporal distance value of 4, B₂ isselected as the source picture for encoding a number (e.g., one or more)of subsequent multimedia pictures. The preselected temporal distancevalue is updated to 2, and the at least one motion parameter is updatedto at least one motion parameter determined from the selected sourcepicture B₂. Similarly, the multimedia pictures B₂, B₆, B₁, B₃, B₅, andB₇ are selected as source pictures for computing at least one motionestimation parameter to be implemented for motion estimation of thesubsequent multimedia pictures B₆, B₁, B₃, B₅, B₇, and P₁₆ in theencoding order 406, respectively.

The multimedia picture P₁₆ is encoded, such as, for example, by theencoding module 208, based on the at least motion parameter that isdetermined from the selected source picture B₇. Upon or subsequent to anencoding of P₁₆, the processor module 202 computes at least one temporaldistance between P₁₆ and one or more reference pictures associated withP₁₆ in the capture order sequence 302. According to the capture ordersequence 302, the reference picture for P₁₆ is P₈, and, accordingly, thetemporal distance value is computed to be 8 in the forward referenceregion. Accordingly, the minimum temporal distance is computed to be 8.The minimum temporal distance of 8 is compared with the updatedpreselected temporal distance value of 1 (which corresponds to themultimedia picture B₇), and, upon or subsequent to determining thatminimum temporal distance value is greater than the updated preselectedtemporal distance value of 1, P₁₆ is not selected as the source picturefor encoding a number (e.g., one or more) of subsequent multimediapictures. The preselected temporal distance value remains to be 1, andthe at least one motion parameter remains to be at least one motionparameter determined from the previously selected source picture B₇.

Subsequently, a multimedia picture B₁₂ is encoded, such as, for example,by the encoding module 208, based on the at least one motion parameterdetermined from the source picture B₇. Upon or subsequent to an encodingof B₁₂, the processor module 202 computes at least one temporal distancebetween B₁₂ and one or more reference pictures associated with B₁₂ inthe capture order sequence 302. According to the capture order sequence302, the reference pictures for B₁₂ are P₈ and P₁₆, and, accordingly,the temporal distance values are computed to be 4 in both the forwardand backward reference regions. Accordingly, the minimum temporaldistance is computed to be 4. The minimum temporal distance of 4 iscompared with the updated preselected temporal distance value of 1, and,upon or subsequent to determining that the minimum temporal distancevalue is greater than the updated preselected temporal distance value of1, B₁₂ is not selected as the source picture for encoding a number(e.g., one or more) of subsequent multimedia pictures. The preselectedtemporal distance value remains to be 1, and the at least one motionparameter remains to be at least one motion parameter determined fromthe source picture B₇.

Similarly, the multimedia picture B₇ is utilized as the source picturefor computing at least one motion estimation parameter to be implementedfor motion estimation of the subsequent multimedia pictures B₁₀, B₁₄,and B₉ in the encoding order 406, and the multimedia picture B₉, B₁₁,and B₁₃ are utilized as the source pictures for computing at least onemotion estimation parameter to be implemented for motion estimation ofthe subsequent multimedia pictures B₁₁, B₁₃, and B₁₅, respectively, inthe encoding order 406. The motion estimation parameters computed basedon the scheme 400 of FIG. 4 are reliable, and, accordingly, the scheme400 leads to an improvement in overall video compression efficiency. Thescheme 400 of FIG. 4 is implementable in progressive multimedia content.However, for interlaced multimedia content, the preselected temporaldistance value is maintained at a value that is greater than or equal totwo temporal distance units such that an optimal video compressionefficiency may be achieved. In an embodiment, an encoding of aninterlaced multimedia content may involve an adaptive field referencingpattern encoding of multimedia pictures. A source picture selectionscheme that may be implemented to estimate motion in interlacedmultimedia content subjected to encoding based on the adaptive fieldreferencing pattern is described further herein with reference to FIG.5.

FIG. 5 is a schematic view illustrating an exemplary adaptive fieldreferencing pattern 500 that may be implemented to encode interlacedmultimedia content, according to an embodiment. The interlacedmultimedia content of FIG. 5 includes a plurality of multimedia framesincluding, for example, frame N 502, frame N+1 504, frame N+2 506, andframe N+3 508 in a capture order, wherein N is a positive integer. Eachmultimedia frame from among the plurality of multimedia frames (e.g.,frames 502-508) includes a top field (e.g., top fields 502 a, 504 a, 506a, and 508 a) and a bottom field (e.g., bottom fields 502 b, 504 b, 506b, and 508 b). The plurality of multimedia frames (e.g., frames 502-508)are captured in an order starting from the top field 502 a, followed bythe bottom field 502 b, the top field 504 a, the bottom field 504 b, thetop field 506 a, the bottom field 506 b, the top field 508 a, and thebottom field 508 b. The adaptive field referencing pattern 500 depictedin FIG. 5 toggles between a most recently coded field (MRF) referencingpattern and a same parity field (SPF) referencing pattern.

In the adaptive field referencing pattern 500, a reference field mayeither be the MRF or the SPF. The adaptive field referencing pattern 500comprises the MRF when a top field is encoded based on a bottom field,and vice versa, wherein the top field and the bottom field belong to thesame or different multimedia frames. In the adaptive field referencingpattern 500 of FIG. 5, the arrows, such as arrows 510, illustrate adependence (or an association) of a field on (or with) another field,such that a reference field for encoding purposes is established.

As indicated by the arrows 510, the bottom field 502 b of frame N 502 isencoded by referencing the top field 502 a of the frame N 502, the topfield 504 a of frame N+1 504 is encoded by referencing the bottom field504 b of the frame N 502, and the bottom field 504 b of the frame N+1504 is encoded by referencing the top field 504 a of the frame N+1 504.The top field 502 a and the bottom field 502 b of the frame N 502 andthe top field 504 a and the bottom field 504 b of the frame N+1 504 areconsequently MRFs. The adaptive field referencing pattern 500constitutes the SPF when a top field of a first frame is encoded basedon a top field of a second frame, and a bottom field of the first frameis encoded based on a bottom field of the second frame. Accordingly,each of the top field 506 a of frame N+2 506, the top field 508 a offrame N+3 508, the bottom field 506 b of frame N+2 506, and the bottomfield 508 b of frame N+3 508 are SPFs. As explained earlier herein withreference to FIGS. 3 and 4, in order to select at least one motionestimation parameter so as to estimate a motion of each of the pluralityof multimedia frames (e.g., 502-508), the processor module 202 receivesthe plurality of multimedia frames (e.g., 502-508) in the capture order.Initially, at least one preselected motion estimation parameter is setto minimum initial values (e.g., (0, 0), wherein each of the temporalpredictors and the mean motion vector are set to a value of 0).

The processor module 202 receives the top field 502 a, and the encodingmodule 208 or the multimedia encoder encodes the top field 502 a basedon the minimum initial values (e.g., (0, 0)) of the preselected motionestimation parameter. Upon or subsequent to receiving the bottom field502 b, the processor module 202 selects the top field 502 a as a sourcepicture for computing at least one motion estimation parameter to beimplemented for estimating a motion of the bottom field 502 b. Themotion estimation module 204 computes at least one motion estimationparameter for the bottom field 502 b based on the top field 502 a. Themotion estimation module 204 estimates motion in the bottom field 502 bbased on the computed at least one motion estimation parameter.Subsequent to estimating motion in the bottom field 502 b, the encodingmodule 208 encodes the bottom field 502 b. Upon or subsequent toreceiving the top field 504 a, the processor module 202 computes atemporal distance between the previously encoded bottom field 502 b andthe top field 502 a. The temporal distance between the bottom field 502b and the top field 502 a is one temporal distance unit. The processormodule 202 compares the temporal distance with a preselected temporaldistance value that is substantially equivalent to two temporal distanceunits. The temporal distance between the bottom field 502 b and the topfield 502 a of one temporal distance unit less than the preselectedtemporal distance value of two temporal distance units.

Consequently, the processor module 202 selects the bottom field 502 b asa source picture for computing at least one motion estimation parameterfor motion estimation of the top field 504 a. The motion estimationmodule 204 determines at least one motion estimation parameter based onthe selected bottom field 502 b and estimates motion in the top field504 a based on the determined at least one motion estimation parameter.Based on the motion estimation, encoding module 208 encodes the topfield 504 a. The motion estimation module 204 updates the preselected atleast one motion estimation parameter to the motion estimation parametercomputed from the bottom field 502 b such that motion in the subsequentfields may be estimated. The temporal distance between each of the SPFsand the corresponding reference fields is two temporal distance units inthe capture order. By maintaining the preselected temporal distancevalue at two temporal distance units and not updating the preselectedtemporal distance value during every iteration of motion estimation, thesource pictures selected by the processor module 202 will be arranged orpositioned (upon or subsequent to a transition from an MRF to an SPF(e.g., upon or subsequent to receiving the bottom field 506 b)) in thevicinity of the fields to be motion estimated. In so much as the sourcefields are selected in the vicinity of the fields to be motionestimated, a recurrence of the source pictures in or during a motionestimation of subsequent fields is prevented, thereby improving (1) thereliability of the motion estimation parameters that are computed and(2) overall video compression efficiency.

For example, upon or subsequent to receiving the bottom field 506 b, theprocessor module 202 computes a temporal distance between the top field506 a and the top field 504 a that is referenced by the top field 506 a.The processor module 202 determines that the computed at least onetemporal distance is two temporal distance units. The processor module202 compares the computed at least one temporal distance of two temporaldistance units with the preselected temporal distance value of twotemporal distance units. In so much as the computed at least onetemporal distance is equal to the preselected temporal distance unit,the processor module 202 selects the top field 506 a as the sourcepicture for the bottom field 506 b. The motion estimation module 204computes at least one motion estimation parameter for the bottom field506 b based on the top field 506 a selected as the source picture. Themotion estimation module 204 estimates the motion of the bottom field506 b based on the computed at least one motion estimation parameter.Furthermore, the motion estimation module 204 updates the preselected atleast one motion estimation parameter by changing the value of thepreselected at least one motion estimation parameter to the value of thedetermined at least one motion estimation parameter based on the topfield 506 a. Similarly, at least one motion estimation parameter that iscomputed based on frame N+1 is used for a motion estimation of frameN+2, and at least one motion estimation parameter that is computed basedon frame N+2 is used for a motion estimation of frame N+3, and so on.

FIGS. 6A and 6B illustrate an improvement of a perceptual multimediaquality on performing a source picture selection as explained in FIG. 4,pursuant to an exemplary scenario. In particular, FIG. 6A depicts a pairof peak signal to noise ratio (PSNR) traces including a first PSNR trace602 and a second PSNR trace 604 according to an embodiment. Each of thefirst PSNR trace 602 and the second PSNR trace 604 is a plot of PSNRobserved across a plurality of multimedia pictures. The first PSNR trace602 and the second PSNR trace 604 may be distinguished based on anexemplary point line trace 605. In FIG. 6A, a reference index ofpictures corresponding to the multimedia pictures is plotted on theX-axis 606, and the corresponding PSNR is plotted on the Y-axis 608. Thefirst PSNR trace 602 corresponds to a plot of variation in PSNR observedfor motion estimation performed based on a scheme of encoding eachmultimedia picture based on the most recently encoded P-picture, and thesecond PSNR trace 604 corresponds to a plot of variation in PSNRobserved for motion estimation performed based the source pictureselection as explained in FIG. 4.

For purposes of illustration, the following exemplary PSNR values arelisted along the Y-axis axis 608: 35, 36, 37, 38, 39, 40, 41, 42, 43,44, and 45. Additionally, for purposes of illustration, the followingexemplary reference indices corresponding to the multimedia pictures arelisted along the X-axis 606: 1, 4, 7, 10, 13, 16, 19, 22, 25, 28, 31,34, 37, 40, 43, 46, 49, 52, 55, and 58. It can be observed that thesecond PSNR trace 604 achieves a significantly higher PSNR than thefirst PSNR trace 602 for most of the multimedia pictures. The motionestimation performed based on source picture selection of FIG. 4improves the PSNR, thereby improving a perceptual multimedia quality.The improvement in the perceptual multimedia quality may be assessedbased on a reduction in visible artifacts caused by a degradation ofdecoded multimedia data due to the encoding or decoding processes.

FIG. 6B illustrates exemplary bit rate traces associated with theencoding of multimedia data pursuant to an exemplary scenario. A bitrate trace is a plot of a variation in a number of bits consumed duringthe encoding of a plurality of multimedia pictures. In FIG. 6B, areference index of the multimedia pictures is plotted on the X-axis 612,and the corresponding number of bits consumed is plotted on the Y-axis614. For purposes of illustration, the following exemplary bit ratevalues (in units of bits per second) are listed along the Y-axis 614: 0,20000, 40000, 60000, 80000, 100000, 120000, 140000, 160000, 180000, and200000. Additionally, for purposes of illustration, the followingexemplary reference indices corresponding to the multimedia pictures arelisted along the X-axis 612: 1, 4, 7, 10, 13, 16, 19, 22, 25, 28, 31,34, 37, 40, 43, 46, 49, 52, 55, and 58. The exemplary bit rate traces ofFIG. 6B include a first bit rate trace 616 and a second bit rate trace618. The first bit rate trace 616 and the second bit rate trace 618 maybe distinguished based on an exemplary point line trace 620. The firstbit rate trace 616 corresponds to multimedia pictures encoded based on amotion estimation performed using a previously encoded P-picture. Asecond bit trace 618 corresponds to an encoding of multimedia picturesbased on the source picture selection of FIG. 4. It may be observed thatthe second bit trace 618 achieves lower bit rates when compared to thefirst bit rate trace 616. The source picture selection of FIG. 4 resultsin a reduction in the bit-rate, thereby leading to an improvement inmultimedia quality. A method of performing a motion estimation of aplurality of multimedia pictures is explained herein with reference toFIG. 7.

FIG. 7 is a flow diagram of a method 700 for estimating motion in aplurality of multimedia pictures according to an embodiment. The method700 may be performed by a processor which may include a multi-coreprocessor, a single core processor, or combination of multi-coreprocessors and single core processors. In an example embodiment, theprocessor may be embodied as one more of a microprocessor, a controller,a digital signal processor (DSP), processing circuitry with or withoutan accompanying DSP, or various other processing devices includingintegrated circuits such as, for example, an application specificintegrated circuit (ASIC), a field programmable gate array (FPGA), amicrocontroller unit (MCU), a hardware accelerator, a special-purposecomputer chip, or the like. In an example embodiment, the processor maybe configured to perform functions that are depicted to be implementedthrough modules, such as processor module 202, motion estimation module204 and encoding module 208 of FIG. 2. Examples of the plurality ofmultimedia pictures may include, for example, multimedia frames,multimedia fields, and the like. The plurality of multimedia picturesmay be associated with, for example, a progressive multimedia content,an interlaced multimedia content, and the like. The method 700 starts atoperation 702. At operation 702, at least one temporal distance betweena multimedia picture and one or more reference pictures corresponding tothe multimedia picture in a capture order associated with the pluralityof multimedia pictures is computed. The computation of the at least onetemporal distance may be performed as explained herein with reference toFIG. 3.

Furthermore, a minimum temporal distance from among the at least onetemporal distance between the multimedia picture and the one or morereference pictures is determined. For example, if the multimedia pictureis a B-picture, the multimedia picture includes a pair of referencepictures and, correspondingly, is associated with a pair of temporaldistances corresponding to the pair of reference pictures (e.g., a firsttemporal distance between the B-picture and a first reference pictureand a second temporal distance between the B-picture and a secondreference picture). The lesser of the first temporal distance and thesecond temporal distance is computed as the minimum temporal distance.The minimum temporal distance is compared with a preselected temporaldistance value. Upon or subsequent to determining that the minimumtemporal distance is less than or equal to the preselected temporaldistance value, the multimedia picture is selected as a source picturefor computing at least one motion estimation parameter for motionestimation in the subsequent multimedia picture.

At operation 704, at least one motion estimation parameter is determinedbased on the at least one temporal distance. The motion estimationparameter includes, but is not limited to, a set of temporal predictorsand/or a mean motion vector. The mean motion vector (e.g. a globalmotion vector) corresponds to a mean, or average, of all motion vectorsin one or more regions of interest (e.g., one or more rows of macroblocks) of a source picture selected for computing the at least onemotion estimation parameter for estimating motion in a subsequentmultimedia picture. Upon or subsequent to a selection of the multimediapicture as the source picture, the at least one motion estimationparameter is computed from the multimedia picture. In an embodiment, theat least one motion estimation parameter is determined based on abackward reference picture (e.g., a temporally succeeding referencepicture in an encoding order) associated with the multimedia picturethat is selected as the source picture. In an embodiment, the at leastone motion estimation parameter is determined based on a forwardreference picture (e.g., a temporally preceding reference picture in theencoding order) associated with the multimedia picture that is selectedas the source picture.

In an embodiment, upon or subsequent to a selection of the multimediapicture, the preselected temporal distance value is updated to a valuecorresponding to the minimum temporal distance. In an embodiment, thepreselected at least one motion estimation parameter is updated to atleast one motion estimation parameter computed from the selectedmultimedia picture upon or subsequent to a selection of the multimediapicture. In an embodiment, upon or subsequent to the plurality ofmultimedia pictures being associated with interlaced multimedia content,an adaptive field referencing pattern is selected for encoding. Upon orsubsequent to a selection of an adaptive field referencing pattern thatmay be implemented to encode the plurality of multimedia pictures, thepreselected temporal distance value is chosen to be greater than orequal to two temporal distance units. Also, upon or subsequent to aselection of the multimedia picture as the source picture, thepreselected at least one motion estimation parameter is updated whilethe preselected temporal distance value is maintained at a value greaterthan or equal to two temporal distance units, as described herein withreference to FIG. 5.

At operation 706, motion associated with a subsequent multimedia pictureto be encoded is estimated based on the at least one motion estimationparameter including the updated at least one preselected motionestimation parameter (e.g., upon or subsequent to selection of themultimedia picture as the source picture). Upon or subsequent todetermining that the minimum temporal distance is greater than apreselected temporal distance value, the motion associated with thesubsequent multimedia picture is estimated based on at least onepreselected motion estimation parameter, as explained herein withreference to FIGS. 3 and 4. The subsequent multimedia picture is encodedbased on the estimated motion associated with the subsequent multimediapicture. A source picture may be selected for each multimedia picturefrom among a plurality of subsequent multimedia pictures and at leastone motion estimation parameter determined from the selected sourcepicture may be implemented to encode subsequent multimedia pictures, asexplained herein with reference to FIG. 4. A method of selecting atleast one motion estimation parameter is explained herein with referenceto FIGS. 8A-8B.

FIGS. 8A-8B depict a flow diagram of a method 800 of source pictureselection that may be implemented to estimate motion associated with aplurality of multimedia pictures, according to an embodiment. Theplurality of multimedia pictures may include, multimedia frames, fields,and the like. Also the plurality of multimedia pictures may beassociated with a progressive multimedia content, an interlacedmultimedia content, and the like. The method 800 starts at operation802. At operation 802, a minimum temporal distance from among at leastone temporal distance between the multimedia picture and the one or morereference pictures is determined (e.g., using processor module 202 ofFIG. 2). The minimum temporal distance is computed subsequent toencoding of the multimedia picture. The computation of the minimumtemporal distance may be performed as explained in FIG. 3.

At operation 804, the minimum temporal distance is compared with apreselected temporal distance value. If the minimum temporal distance isless than or equal to the preselected temporal distance value, thenoperation 806 is performed. If the minimum temporal distance value isgreater than the preselected temporal distance value then operation 810is performed.

At operation 806, upon or subsequent to determining the minimum temporaldistance to be less than or equal to the preselected temporal distancevalue, the multimedia picture is selected as a source picture forcomputing at least one motion estimation parameter for motion estimationin a subsequent multimedia picture. The selection of the multimediapicture as the source picture may be performed as explained in FIG. 4.At operation 808, the at least one motion estimation parameter iscomputed (e.g., using motion estimation module 204 of FIG. 2) from themultimedia picture upon or subsequent to selection of the multimediapicture as the source picture. In an embodiment, the at least one motionestimation parameter is determined based on a backward reference picture(a temporally succeeding reference picture in an encoding order)associated with the multimedia picture selected as the source picture.In an embodiment, the least one motion estimation parameter isdetermined based on a forward reference picture (a temporally precedingreference picture in the encoding order) associated with the multimediapicture selected as the source picture. At operation 810, motionassociated with the subsequent multimedia picture is estimated (e.g.,using motion estimation module 204 of FIG. 2) based on a preselected atleast one motion estimation parameter upon or subsequent to determiningthe minimum temporal distance to be greater than a preselected temporaldistance value.

At operation 812, the preselected temporal distance value is updated(e.g., using motion estimation module 204 of FIG. 2) to a valuecorresponding to the minimum temporal distance and/or the preselected atleast one motion estimation parameter is updated to at least one motionestimation parameter computed from the selected multimedia picture. Inan embodiment, upon or subsequent to the multimedia picture including afield associated with an interlaced multimedia content, the preselectedat least one motion estimation parameter alone is updated whilemaintaining the preselected temporal distance value at a value greaterthan or equal to two temporal distance units as explained in FIG. 5.

At operation 814, motion associated with the subsequent multimediapicture is estimated (e.g., using motion estimation module 204 of FIG.2) based on the at least one motion estimation parameter computed fromthe selected multimedia picture. At operation 816, the subsequentmultimedia picture is encoded (e.g., using encoding module 208 of FIG. 2or a multimedia encoder) based on the estimated motion associated withthe subsequent multimedia picture. The encoding may be an interlacedencoding, a progressive encoding, and the like.

Without in any way limiting the scope, interpretation, or application ofthe claims appearing below, advantages of one or more of the exemplaryembodiments disclosed herein include applicability in various codingstructures, including but not limited to, an IBBP coding structure, ahierarchical coding structure, and an IPPP coding structure.Furthermore, various embodiments of the present technology enable adynamic and reliable selection of motion estimation parameters forestimating motion associated with a plurality of multimedia pictures asopposed to other known techniques of selection of motion estimationparameters that use a fixed picture position in a GOP for selection ofthe motion estimation parameters. The present technology results in animproved motion estimation efficiency in multimedia sequences involvinga significant amount of change between the multimedia pictures (e.g.,high motion sequences, gradual scene change sequences, or sequences witha large GOP size). Also, the method disclosed herein is computationallysimple to be implemented in a multimedia encoder, with the need tomerely change one or more frame level operations, hardly impacting thereal time performance of the multimedia encoder.

Additionally, the usage of the present technology leads to a gain inpeak signal to noise ratio. Moreover, the methods and systems disclosedherein help reduce a search range and thereby achieve the best qualityin a given scheme. The reduction in the search range results in loweringan amount of reference data transferred and/or an internal memory footprint of a reference region. Also, the reduction in the search rangeleads to a lot of savings in a memory transfer rate for each macroblock, the savings being more pronounced in higher resolution. Themethods and systems of the present technology result in both reductionof bit-rate as well as improvement in a multimedia quality.

Although the present technology has been described with reference tospecific exemplary embodiments, it is noted that various modificationsand changes may be made to these embodiments without departing from thebroad spirit and scope of the present technology. For example, thevarious devices, modules, analyzers, generators, etc., described hereinmay be enabled and operated using hardware circuitry (e.g.,complementary metal oxide semiconductor (CMOS) based logic circuitry),firmware, software and/or any combination of hardware, firmware, and/orsoftware (e.g., embodied in a machine readable medium). For example, thevarious electrical structures and methods may be embodied usingtransistors, logic gates, and electrical circuits (e.g., applicationspecific integrated circuit (ASIC) circuitry and/or in Digital SignalProcessor (DSP) circuitry).

Particularly, the system 200, the processor module 202, the motionestimation module 204, the memory module 206, and the encoding module208 of FIG. 2 may be enabled using software and/or using transistors,logic gates, and electrical circuits (e.g., integrated circuit circuitrysuch as ASIC circuitry). Embodiments of the present disclosure includeone or more computer programs stored or otherwise embodied on acomputer-readable medium, wherein the computer programs are configuredto cause a processor to perform one or more operations. Acomputer-readable medium storing, embodying, or encoded with a computerprogram, or similar language, may be embodied as a tangible data storagedevice storing one or more software programs that are configured tocause a processor to perform one or more operations. Such operations maybe, for example, any of the steps or operations described herein.Additionally, a tangible data storage device may be embodied as one ormore volatile memory devices, one or more non-volatile memory devices,and/or a combination of one or more volatile memory devices andnon-volatile memory devices.

Also, techniques, devices, subsystems and methods described andillustrated in the various embodiments as discrete or separate may becombined or integrated with other systems, modules, techniques, ormethods without departing from the scope of the present technology.Other items shown or discussed as directly coupled or communicating witheach other may be coupled through some interface or device, such thatthe items may no longer be considered directly coupled with each otherbut may still be indirectly coupled and in communication, whetherelectrically, mechanically, or otherwise, with one another. Otherexamples of changes, substitutions, and alterations ascertainable by oneskilled in the art, upon or subsequent to studying the exemplaryembodiments disclosed herein, may be made without departing from thespirit and scope of the present technology.

It should be noted that reference throughout this specification tofeatures, advantages, or similar language does not imply that all of thefeatures and advantages should be or are in any single embodiment.Rather, language referring to the features and advantages may beunderstood to mean that a specific feature, advantage, or characteristicdescribed in connection with an embodiment may be included in at leastone embodiment of the present technology. Thus, discussions of thefeatures and advantages, and similar language, throughout thisspecification may, but do not necessarily, refer to the same embodiment.

Various embodiments of the present disclosure, as discussed above, maybe practiced with steps and/or operations in a different order, and/orwith hardware elements in configurations which are different than thosewhich are disclosed. Therefore, although the technology has beendescribed based upon these exemplary embodiments, it is noted thatcertain modifications, variations, and alternative constructions may beapparent and well within the spirit and scope of the technology.Although various exemplary embodiments of the present technology aredescribed herein in a language specific to structural features and/ormethodological acts, the subject matter defined in the appended claimsis not necessarily limited to the specific features or acts describedabove. Rather, the specific features and acts described above aredisclosed as exemplary forms of implementing the claims.

What is claimed is:
 1. A method comprising: computing, with a processor,a temporal distance between a picture in a sequence of video picturesand one or more reference pictures in the sequence of video pictures,the reference pictures being used to perform motion compensation for thepicture; determining whether the temporal distance computed for thepicture is less than or equal to a minimum temporal distance value, theminimum temporal distance value being less than or equal to temporaldistances computed for all previously coded pictures in the sequence ofvideo pictures; selecting, with the processor, the picture as a sourcepicture for obtaining seed predictors to use when performing motionestimation for a subsequent picture in response to determining that thetemporal distance is less than or equal to the minimum temporal distancevalue; selecting, with the processor, a current source picture as thesource picture for obtaining the seed predictors to use when performingthe motion estimation for the subsequent picture in response todetermining that the temporal distance is not less than or equal to theminimum temporal distance value, the current source picturecorresponding to a source picture used for obtaining seed predictors forthe picture; and performing, with the processor, the motion estimationfor the subsequent picture based on the seed predictors obtained fromthe selected source picture.
 2. The method of claim 1, whereinperforming the motion estimation includes: computing the seed predictorsbased on the source picture.
 3. The method of claim 1, furthercomprising updating at least one of: the minimum temporal distance valueto a value corresponding to the temporal distance for the picture; and amotion estimation parameter to a motion estimation parameter computedfrom the selected source picture.
 4. The method of claim 1, whereinperforming the motion estimation includes determining a motion vectorfor the subsequent picture, the method further comprising: encoding thesubsequent picture based on the motion vector for the subsequentpicture.
 5. The method of claim 1, wherein the minimum temporal distancevalue is greater than or equal to two temporal distance units for anadaptive field referencing pattern encoding of pictures.
 6. The methodof claim 1, wherein the seed predictors include at least one of a set oftemporal predictors and a mean motion vector, wherein the mean motionvector corresponds to a mean of all motion vectors in one or moreregions of interest of the source picture selected for the subsequentpicture.
 7. A computer implemented method comprising: computing, with aprocessor, a temporal distance between a picture in a sequence of videopictures and one or more reference pictures in the sequence of videopictures, the reference pictures being used to perform motioncompensation for the picture; determining, with the processor, whetherthe temporal distance computed for the picture is less than or equal toa minimum temporal distance value, the minimum temporal distance valuebeing less than or equal to temporal distances computed for allpreviously coded pictures in the sequence of video pictures; selecting,with the processor, a source picture for obtaining seed predictors touse when performing motion estimation for a subsequent picture based onwhether the temporal distance computed for the picture is less than orequal to the minimum temporal distance value; and performing, with theprocessor, the motion estimation for the subsequent picture based on theseed predictors obtained from the selected source picture.
 8. Thecomputer implemented method of claim 7, wherein performing the motionestimation includes: computing the seed predictors based on the sourcepicture.
 9. The computer implemented method of claim 7, furthercomprising: updating the minimum temporal distance value to a valuecorresponding to the minimum temporal distance for the picture.
 10. Thecomputer implemented method of claim 7, wherein performing the motionestimation includes determining a motion vector for the subsequentpicture, the method further comprising: encoding the subsequent picturebased on the motion vector for subsequent picture.
 11. The computerimplemented method of claim 8, wherein the seed predictors include atleast one of a set of temporal predictors and a mean motion vector,wherein the mean motion vector corresponds to a mean of all motionvectors in one or more regions of interest of the source pictureselected for the subsequent picture.
 12. A system comprising: aprocessor circuit configured to: compute a temporal distance between apicture in a sequence of video pictures and one or more referencepictures in the sequence of video pictures, the reference pictures beingused to perform motion compensation for the picture; determine whetherthe temporal distance computed for the picture is less than or equal toa minimum temporal distance value, the minimum temporal distance valuebeing less than or equal to temporal distances computed for all thepreviously coded pictures in the sequence of video pictures; select oneor more seed predictors to use when performing motion estimation for asubsequent picture based on whether the temporal distance computed forthe picture is less than or equal to a minimum temporal distance value;and perform the motion estimation for the subsequent picture based onthe determined seed predictors.
 13. The system of claim 12, wherein theprocessor circuit is further configured to: select a source picture usedfor determining the seed predictors based on whether the temporaldistance computed for the picture is less than or equal to a minimumtemporal distance value; and compute the seed predictors based on thesource picture.
 14. The system of claim 12, wherein the processorcircuit is further configured to update the minimum temporal distancevalue to a value corresponding to the temporal distance for the picture.15. The system of claim 12, wherein the processor circuit is furtherconfigured to: determine a motion vector for the subsequent picture; andencode the subsequent picture based on the motion vector for thesubsequent picture.
 16. The system of claim 12, wherein the minimumtemporal distance value is greater than or equal to two temporaldistance units for an adaptive field referencing pattern encoding ofpictures.
 17. The system of claim 13, wherein the seed predictorsinclude at least one of a set of temporal predictors and a mean motionvector, wherein the mean motion vector corresponds to a mean of allmotion vectors in one or more regions of interest of the source pictureselected for the subsequent picture.